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Robust speech perception and classification-driven deep convolutional neural network with natural language processing

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Alexandria Engineering Journal 2025年 123卷 358-368页

作者： Alshammari, Alya Alzaidi, Muhammad Swaileh A. Alrusaini, Othman Alshuhail, Asma Allafi, Randa Yafoz, Ayman Alsini, Raed Khadidos, Alaa O. Department of Applied Linguistics College of Languages Princess Nourah bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia Department of English Language College of Language Sciences King Saud University P. O. Box 145111 Riyadh Saudi Arabia Department of Engineering and Applied Sciences Applied College Umm Al-Qura University Makkah Saudi Arabia Department of Information Systems College of Computer Sciences & Information Technology King Faisal University Saudi Arabia Department of Computer Science College of Sciences Northern Border University Arar Saudi Arabia Department of Information Systems Faculty of Computing and Information Technology King Abdulaziz University Jeddah Saudi Arabia

Speech recognition systems use computer algorithms to interpret and process spoken words and translate them into text. Speech-to-text, or Speech detection, is the proficiency of a program or machine to find spoken words aloud and translate them into plain text. Speech detection systems are the most common complex systems that use wide-ranging research in computer engineering, linguistics, and computer science. In today's significant data era, several machine learning (ML) approaches for processing raw, unlabelled speech data still need to be improved. Deep learning (DL) models, on the other hand, with their powerful modelling ability for extensive data, are capable of directly processing unlabelled data and have become a crucial area of research in the domain of automated speech recognition. The DL model has recently gained popularity for voice disorders and automated speech detection. DL is an ML that exploits artificial neural networks (ANN) to gain meaningful insights from data. The DL approach demonstrated great success and achieved significant attention in different fields comprising speech processing, computer vision (CV), and natural language processing (NLP). Therefore, this article develops a Deep Learning with Natural Language Processing based Robust Speech Detection (DLNLP-RSD) technique. The DLNLP-RSD technique derives features from the mel-frequency cepstral coefficient (MFCC) technique. Followed by the DLNLP-RSD technique employs a one-dimensional deep convolutional neural network (CNN) approach for the detection and classification of speech. Moreover, the parameter tuning model uses the grasshopper fractals optimization algorithm (GOA) approach. The performance evaluation of the proposed technique highlights its significant performance over other models concerning distinct measures. An extensive simulation analysis is executed to examine the improved results of the DLNLP-RSD model. The experimental validation of the DLNLP-RSD technique portrayed a sup

关键词： Convolutional neural networks

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Assessing Students' Perceptions of Academic Quality in Higher Education Using Deep Belief Networks 3

Assessing Students' Perceptions of Academic Quality in Highe...

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3rd International Conference on Integrated Circuits and Communication Systems, ICICACS 2025

作者： Shukla, Rakhi Sushma Garlapati, Bhavani Parasar, Anuradha Pavan Kumar, B. Jayalakshmi, V. Umanesan, R. The Icfai University Icfai Business School Department of Management Dehradun India Koneru Lakshmaiah Education Foundation Department of English Hyderabad India Galgotias University Department of Liberal Education Greater Noida India Department of English and Foreign Languages Bhimavaram India Rmk College of Engineering and Technology Department of English Chennai India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology School of Computing Department of Computer Science Engineering Tiruvalluvar India

ISBN: (纸本)9798331508456

The main objectives of this study are to evaluate a perceived service quality measuring scale and assess college student satisfaction. Administratively, this service quality research focuses on the registrar, schools, faculty, library, residence halls, rector, sports facility, and health centre. Descriptive and causal studies examine the scale's reliability and dimensionality. The suggested methodology includes preprocessing, feature extraction, and model training. Mining outcomes increase with data pretreatment, which fixes missing values and removes noise. Four meta-heuristic optimization methodologies yielded critical student happiness predictors. The model was trained using a DBN. Compared to ELM and ANN, the recommended model has 93.46% accuracy. Results reveal that preprocessing and tuning improved the model's prediction performance. As shown in this proposed, data preprocessing and feature extraction are essential for service quality assessments. The approach suggests a robust foundation for measuring and improving college student services compared to standard methods. © 2025 IEEE.

关键词： Students

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A Comprehensive Survey on RIS-Enhanced Physical Layer Security in UAV-Assisted Networks

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IEEE Internet of Things Journal 2025年

作者： Ahmed, Manzoor Soofi, Aized Amin Raza, Salman Li, Yongxiao Khan, Feroz Khan, Wali Ullah Asif, Muhammad Han, Zhu School of Computer and Information Science China Hubei Engineering University Institute for AI Industrial Technology Research Xiaogan City 432000 China National University of Modern Languages Department of Computer Science Faisalabad 38000 Pakistan National Textile University Department of Computer Science Faisalabad 38000 Pakistan Beijing University of Posts and Telecommunications School of Electronic Engineering Beijing China Gachon University School of Computing Seongnam-si 13120 South Korea School of Computer Science Department of Electrical and Computer Engineering United States University of Houston Department of Electrical and Computer Engineering Houston 77004 TX United States Kyung Hee University Department of Computer Science and Engineering Seoul 446-701 South Korea

This survey provides an in-depth examination of the role of reconfigurable intelligent surfaces (RIS) in enhancing physical layer security (PLS) within unmanned aerial vehicle (UAV)-assisted networks, which are essential for the secure and efficient operation of sixth-generation (6G) wireless communications. The study covers various types of RIS—passive, active, and hybrid—and their applications in both terrestrial and aerial environments to strengthen PLS. Key focus areas include advanced PLS techniques such as optimizing UAV trajectory, beamforming, and RIS phase-shift configurations, all aimed at improving secrecy rates (SRs) while mitigating the risks of eavesdropping and jamming. Moreover, the survey also addresses strategies for enhancing energy-efficient SRs and implementing anti-jamming mechanisms within UAV-assisted networks. Additionally, it explores the integration of RIS-UAV systems with emerging technologies such as non-orthogonal multiple access (NOMA), mobile edge computing (MEC), cognitive radio, and THz networks, demonstrating how security can be enhanced in such networks. Through detailed performance analysis, the paper highlights the transformative potential of RIS-equipped UAVs in overcoming the potential security challenges for future 6G networks. Finally, the survey presents lessons learned and identifies critical future research directions and open challenges, offering insights that will guide the development of robust and secure RIS-assisted UAV systems in next-generation wireless networks. © 2014 IEEE.

关键词： 6G AI physical layer security reconfigurable intelligent surfaces UAV

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Assessing Students' Perceptions of Academic Quality in Higher Education Using Deep Belief Networks

Assessing Students' Perceptions of Academic Quality in Highe...

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Integrated Circuits and Communication Systems (ICICACS), IEEE International Conference on

作者： Rakhi Shukla Bhavani Sushma Garlapati Anuradha Parasar B. Pavan Kumar Jayalakshmi V Umanesan. R Department of Management ICFAI Business School The ICFAI University Dehradun India Department of English Koneru Lakshmaiah Education Foundation Hyderabad India Department of Liberal Education Galgotias University Greater Noida India Department of English and Foreign Languages Sagi Rama Krishnam Raju Engineering College (Autonomous) Bhimavaram India Department of English RMK College of Engineering and Technology Chennai India Department of Computer Science Engineering School of Computing Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Tiruvalluvar India

ISBN: (数字)9798331508456

ISBN: (纸本)9798331508463

关键词： Training COVID-19 Pandemics Noise Metaheuristics Data preprocessing Predictive models Feature extraction Data mining Integrated circuit modeling

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A prototype for discovering compositions of semantic web services

A prototype for discovering compositions of semantic web ser...

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3rd Italian Workshop on Semantic Web Applications and Perspectives, SWAP 2006

作者： Brogi, Antonio Corfini, Sara Aldana, José F. Navas, Ismael Department of Computer Science University of Pisa Italy Department of Computer Languages and Computing Science University of Malaga Spain

Semantic Web services provide semantically enhanced service descriptions which allow the development of automated service discovery and composition. Yet, an efficient semantic-based service discovery remains a major open challenge towards a wide acceptance of semantic Web services. In this paper we present a fully-automated matchmaking system for discovering sets of OWL-S Web services capable of satisfying a given client request.

关键词： Web services

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SB-KOM: Integration of pathway information with BioPax

SB-KOM: Integration of pathway information with BioPax

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10th Spanish Symposium on Bioinformatics for Personalized Medicine, JBI 2010

作者： García-Godoy, María Jesús Navas-Delgado, Ismael Aldana-Montes, José F. Computer Languages and Computing Science Department University of Malaga Malaga 29071 Spain

ISBN: (纸本)9783642280610

BioPax Level 3 is a novel approach to describe pathways at a semantic level by means of an owl ontology. Data provided as BioPax instances is distributed in several databases, and so it is difficult to find integrated information as instances of this ontology. Biopax is a biology ontology that aims to facilitate the integration and exchanged data maintained in biological pathways data. In this paper we present an approach to integrate pathway information by means of an ontology-based mediator (SB-KOM). This mediator has been enabled to produce instances of BioPax Level 3 from integrated data. Thus, it is possible to obtain information about a specific pathway extracting data from distributed databases. © 2012 Springer-Verlag.

关键词： Ontology

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A protégé plugin for querying and reasoning on persistent OWL ontologies

A protégé plugin for querying and reasoning on persistent ...

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5th Workshop on Semantic Web Applications and Perspectives, SWAP 2008

作者： Roldan-Garcia, Maria Del Mar Molina-Castro, Joaquin J. Aldana-Montes, Jose F. University of Malaga Computer Languages and Computing Science Department Malaga 29071 Spain

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A tool for storing OWL using database technology

A tool for storing OWL using database technology

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1st Workshop on OWL: Experiences and Directions, OWLED 2005

作者： Del Mar Roldan-Garcia, Maria Aldana-Montes, Jose F. University of Malaga Computer Languages and Computing Science Department Malaga 29071 Spain

This paper presents a tool that helps developers to design and implement storage models for OWL ontologies. This tool uses xml both to represent the knowledge given by the ontology, and define the rules that generate the storage model. It presents a graphical interface that helps developers to use it. The storage models created by this tool will be used in our research studies.

关键词： Ontology

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KASBi: Knowledge-based analysis in systems biology

KASBi: Knowledge-based analysis in systems biology

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Workshop on Semantic Web Applications and Tools for Life sciences, SWAT4LS 2008

作者： Del Mar Roldán-García, Maria Navas-Delgado, Ismael Kerzazi, Amine Chniber, Othmane Molina, Joaquín Aldana-Montes, José F. Computer Languages and Computing Science Department University of Málaga Málaga Spain

The analysis of information in the biological domain is usually focused on the analysis of data from single on-line data sources. Unfortunately, studying a biological process requires having access to disperse, heterogeneous, autonomous data sources. In this context, an analysis of the information is not possible without the integration of such data. This paper describes how KOMF, the Khaos Ontology-based Mediator Framework, is used to retrieve information and crystallize it in a (persistent) Knowledgebase. This information could be further analyzed later (by means of querying and reasoning). These kinds of systems (based on KOMF) will provide users with very large amounts of information (interpreted as ontology instances once retrieved), which cannot be managed using traditional main memory-based reasoners. We propose a methodology for creating persistent and scalable knowledgebases from sets of OWL instances.

关键词： Tools

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Deep crawling in the semantic web: In search of deep knowledge

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5th International Conference on Web Information Systems Engineering, WISE 2004

作者： Navas-Delgado, Ismael del Mar Roldan-Garcia, Maria Aldana-Montes, Jose F. University of Malaga Computer Languages and Computing Science Department Malaga29071 Spain

ISBN: (纸本)3540238948

In this paper we present Deep (Semantic) Crawling, an enhanced crawling methodology. Deep crawling allows for the analysis of semantic mark-ups in both static and dynamic pages This unique capability offers us both a much bigger crawling space (the Deep Web) together with new applications. The paper ends with an use case to highlight the features of Deep Crawling. © Springer-Verlag Berlin Heidelberg 2004.

关键词： Semantic Web

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